Finding novel ways to treat and cure diseases is a fundamental challenge in biomedical research. As reflected by the overall low clinical target validation success rate, there currently exists a general lack of reliable drug target prediction methods. Therefore, new bioinformatics screening approaches are required to accurately predict drug targets for a disease.

Novel drug targets refer to unexploited targets that can be used for developing first-in-class drugs and combination therapies. Network-based methods have been developed for the identification of unknown disease-associated genes.

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How our Technology Works

To address this intrinsic challenge in drug discovery, InMed has developed a proprietary, in silico bioinformatics platform technology, which uses computer algorithms that can reach high-probability conclusions from massive, publicly available databases together with an internal library of cannabinoid drug information. This tool is a “network-based platform” for the identification of novel, plant-based therapies using: (i) comprehensive algorithms to integrate data from numerous bioinformatics databases, (ii) a database on the structure of previously researched pharmaceutical products, and (iii) an extensive database on over 200,000 phytochemicals, including cannabinoids.

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Successes and Future Applications

Our bioinformatics platform has been integral to the identification of our target indications: INM-755 for the treatment of epidermolysis bullosa, INM-085 for the treatment of glaucoma, and INM-405 for the treatment of peripheral pain. In addition, it has also helped us compile a library of other opportunities that are currently earlier in the development pipeline.

InMed’s strategy for the continued advancement of the bioinformatics technology is to:

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